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Peer-to-peer streaming over dynamic random Hamilton cycles

机译:动态随机汉密尔顿周期上的对等流

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We are motivated by the problem of designing a simple distributed algorithm for Peer-to-Peer streaming applications that can achieve high throughput and low delay, while allowing the neighbor set maintained by each peer to be small. While previous works have mostly used tree structures, our algorithm constructs multiple random directed Hamilton cycles and disseminates content over the superposed graph of the cycles. Compared with the algorithms constructing trees, the complexity to dynamically update the network topology in response to peer churn does not increase with the network size under our algorithm. We show that it is possible to achieve the maximum streaming capacity even when each peer only transmits to and receives from Θ(1) neighbors. Further, we show that the proposed algorithm achieves the streaming delay of Θ(logN) when the streaming rate is less than (1 - 1/K) of the maximum capacity for any fixed constant K ≥ 2.
机译:我们对为点对点流应用程序设计一种简单的分布式算法的问题感到兴奋,该算法可以实现高吞吐量和低延迟,同时允许每个对等端维护的邻居集很小。尽管先前的工作主要使用树结构,但我们的算法构造了多个随机有向汉密尔顿循环,并在循环的叠加图中散布了内容。与构造树的算法相比,根据我们的算法,响应对等搅动而动态更新网络拓扑的复杂性不会随网络规模的增加而增加。我们证明,即使每个对等方仅向Θ(1)邻居发送和接收,也有可能实现最大的流传输容量。此外,我们表明,对于任何固定常数K≥2,当流速率小于最大容量的(1-1 / K)时,所提出的算法均可实现Θ(logN)的流延迟。

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